A very fast implementation of 2D iterative reconstruction algorithms

Peter Aundal Toft, Peter James Jensen

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    One of the limitations of using iterative reconstruction methods in tomography is the slow performance compared with the direct reconstruction methods, such as Filtered Backprojection. Here, the authors demonstrate a very fast implementation of most types of iterative reconstruction methods. The key idea of the authors' method is to generate the huge system matrix only once, and store it using sparse matrix techniques. From the sparse matrix one can perform the matrix vector products very fast, which implies a major acceleration of the reconstruction algorithms. Here, the authors demonstrate that iterative reconstruction algorithms can be implemented and run almost as fast as direct reconstruction algorithms. The method has been implemented in a software package that is available for free, providing reconstruction algorithms using ART, EM, and the Least Squares Conjugate Gradient Method
    Original languageEnglish
    Title of host publicationNuclear Science Symposium. Conference Record
    VolumeVolume 3
    Publication date1996
    ISBN (Print)07-80-33534-1
    Publication statusPublished - 1996
    Event1996 IEEE Nuclear Science Symposium and Medical Imaging Conference - Anaheim, United States
    Duration: 2 Nov 19969 Nov 1996


    Conference1996 IEEE Nuclear Science Symposium and Medical Imaging Conference
    Country/TerritoryUnited States
    Internet address

    Bibliographical note

    Copyright: 1996 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE


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